Who would have thought that health care could benefit from sites like Facebook, Google and Amazon one day? Turns out that their technology that converts spoken language into text, recognizes faces and targets advertising is helping doctors combat several lethal diseases.

An example of this is an algorithm developed by Erica Shenoy, an infectious-disease specialist at Massachusetts General Hospital, and Jenna Wiens, a computer scientist and assistant professor of engineering at the University of Michigan, that systematically targets patients most vulnerable to a bacterium, Clostiridium difficile (CDI), that thrives in hospitals and that infects nearly half a million patients per year. Using the algorithm, Shenoy and Wiens can predict a patient’s risk of developing an infection based on their vital signs and other health records. The analysis of Shenoy and Wiens’ CDI algorithm seeks connections between CDI and the circumstances around them. It is based on a data set of 374,000 inpatient admissions to Massachusetts General Hospital and the University of Michigan Health System. The algorithm itself is based on a machine learning principle, a form of artificial intelligence that relies on artificial neural networks that roughly mimic the way animal brains learn. The technology is slowly penetrating the U.S. health care industry, and its well-established predictive powers come after years of experimentation.

Another example is Tempus, a Chicago-based startup that was founded by Eric Lefkofsky in 2012. The enterprise has already earned a spot among the city’s top ten health techs. Lefkofsky is essentially doing something similar to Shenoy and Wiens, only with cancer data he gathers through collaborations with the nation’s NCI-designated Cancer Care Centers as well as academic institutions. Tempus was a reaction to the poorly structured health care records that are plagued by the vast discrepancy between cancer patients’ clinical and molecular data. This rift between collected patient data and the use of that information in designing effective treatments is because not all patient data is accessible. In hopes to bridge the gap between the two, Lefkofsky based Tempus on a software platform that relies on optical character recognition and natural language processing that gathers electronic healthcare records from medical and academic institutions and transforms them into structured data. Tempus essentially centralizes these vast amounts of data and marries them to molecular data, ultimately making it accessible to health care workers, who in turn can make more educated, optimized and personalized cancer therapy decisions.

The advantage of these algorithms is that they can provide a more precise prognosis for the course of a disease. This, in turn has the potential to entirely reshape treatment for progressive diseases as well as address any uncertainties. Furthermore, they can help prognosticate fast-moving infections such as CDI, chronic ailments such as heart failure as well as cancer. Such algorithms, while common in internet commerce, finance and self-driving cars, are yet to be explored to their full potential in the health care sector. It is known, however, that skin cancers (from photographs) and lung cancers can be reliably diagnosed via machine learning algorithms, which can also predict the risk of seizures. In other words, if these platforms are adopted on a broad scale, they have the potential to save lots of time and money – and lives!

“DeepVentricle,” the first medical machine learning algorithm for commercial use by the San Francisco company Arterys was approved by the Food and Drug Administration last year. In a mere 30 seconds, the algorithm is capable of performing a task that doctors typically do by hand in 45 minutes, namely drawing the contours of ventricles from multiple MIR scans of the heart muscle in motion. This is so that blood volume that passes through can be calculated. “It’s automating something that is important—and tedious,” said Carla Leibowitz, Arterys’ head of strategy and marketing.

The potential health care approach overhaul via big data analytics is received with some apprehension. Understandably so – the powerful tool is threatening to take over the role of the health care workers. However, Lefkofsky does not see it as such. With Tempus, he is offering a solution to a problem, namely a more consolidated, clean and educated approach to cancer treatment. With Tempus, he is offering treatment solutions so that doctors and other health care workers have more information about cancer patients’ pasts via data availability. This, in turn, will help them make data-driven treatment decisions for current and future patients based on those who came before.

And the tide of available medical data continues to rise, tantalizing scientists. “Think about all the data we are collecting right now,” Wiens said. “Electronic health records. Hospitalizations. At outpatient centers. At home. We are starting to collect lots of data on personal monitors. These data are valuable in ways we can’t yet know.”

With companies such as Tempus, we are beginning to find out.

About Dr Erica Shenoy

Dr. Erica Shenoy is an infectious disease specialist in Boston, Massachusetts and is affiliated with Massachusetts General Hospital. She received her medical degree from Harvard Medical School and has been in practice between 6-10 years. She is one of 69 doctors at Massachusetts General Hospital who specialize in Infectious Disease.

About Lefkofsky

The Chicago-based entrepreneur is behind several other companies. In addition to Tempus, he co-founded Groupon, Echo Global Logistics, InnerWorkings, Lightbank, Uptake Technologies, and Mediaocean. Lefkofsky’s philanthropic engagements include the Lefkofsky Family Foundation and the Giving Pledge. He also serves as the Chairman of the Board of Trustees of the Steppenwolf Theatre Company that is based in Chicago. He is also on the board of trustees of the Lurie’s Children’s Hospital of Chicago, The Art Institute of Chicago, The Museum of Science and Industry and World Business Chicago. Lefkofsky has held teaching positions at the Kellstadt Graduate School of Business at DePaul University as well as at Northwestern University’s Kellogg School of Management. He is currently an adjunct professor at the University of Chicago’s Booth School of Business. He also authored the book Accelerated Disruption: Understanding the True Speed of Innovation.

Tempus focuses on building the world’s largest library of molecular and clinical data. The company provides services such as genomic sequencing and analysis of molecular and therapeutic data based on which physicians can make real-time, data-driven treatment decisions. As more data is acquired, Tempus’ aim is to offer physicians tools so that each patient is to benefit from the treatment of others who came before them.

For more information on Tempus, please visit tempus.com, Facebook: @TempusLabs and Twitter: @TempusLabs.